In this paper, an Unmanned Aerial System (UAS) navigation solution using the Intel RealSense T265, a commercially available Visual Inertial Odometry device, is developed and presented in conjunction with an Extended Kalman Filter framework. Comparisons of raw and estimated position and yaw angle data from the device are made against ground truth measurements obtained via a motion capture system. Preliminary results from hand-carry tests show promising localization capability as the device continues to gather information about its environment. Further localization improvements may be achievable with varied software configurations. The performance of the Extended Kalman Filter during closed-loop flight is also evaluated, and shows smoothing of noisy measurements from the T265 and generally precise trajectory following capabilities. Future work to extend this characterization shall involve testing the performance of the device across varying flight envelopes, and especially for longer durations.